The process of implementing a damage detection and characterization strategy for engineering structures is generally referred to as structural health monitoring (SHM). When permanent deformation occurs, structural displacement or deformation information is particularly important and it is often more accurate than acceleration measurements in lower-frequency ranges.
Conventional methods for displacement monitoring, which include GPS-based methods and computer vision-based methods, each have their own drawbacks. The cost for survey-level, dual-frequency GPS systems that support sub-centimeter accuracy is still too high for routine use. Meanwhile, single-frequency, low-cost GPS devices that are generally used for navigation purposes are not sufficiently advanced for practical use in SHM applications.
Computer vision-based methods use a video camera (generally in combination with an optical zoom lens and lighting lamps) that capture images of a precision target attached to a location of interest on a structure over time. Non-contact, vision-based systems are available at relatively low cost and significantly reduce the difficulties in providing stationary reference points (a critical challenge for contact-type displacement sensors). Conventional video cameras, however, have a number of drawbacks. The limited resolution of conventional video cameras causes difficulty in identifying high-frequency displacements, which have smaller amplitudes than low-frequency vibrations. At higher resolutions, the maximum frame rates of conventional video cameras are limited to 30-60 frames per second. While those low frame rates may be sufficient for measuring low-frequency and high-amplitude vibrations of long-period structures such as high-rise buildings and long-span cable-supported bridges, higher frame rates are essential for appropriately monitoring the dynamic behavior of many of small-to-mid scale structures. Additionally, anti-aliasing filters are not available for conventional vision-based measuring systems. While a high-speed camera (allowing up to 2000 frames per second) may minimize such aliasing problems, the practical use of such expensive cameras for civil engineering applications is still in question because of the level of cost and the difficulty of achieving real-time processing.
Recent advances in smartphone technologies provide various onboard sensing capabilities. In particular, the embedded cameras included in many smartphones provide higher resolution images and higher frame rates than many conventional video cameras. Moreover, their powerful processors and memories allow for onboard processing capabilities, eliminating the need for additional computers to perform extensive image processing. Meanwhile, because of their many general purpose functions (e.g., cellular telephony, text messaging, or internet access, etc.), smartphones are nearly ubiquitous.
Accordingly, there is a need to measure dynamic and absolute displacement by a smartphone.
While the processing power of currently-available smartphones is increasing, smartphone capabilities are still limited when compared to desktop computing devices that can include hardware and software selected for their proficiency regarding computer vision applications. Therefore, in order to quickly and accurately measure both low-frequency, high-amplitude vibrations and high-frequency, low-amplitude vibrations using currently-available smartphone technology, the process must be optimized.